Fix fcn-resnet50-12 accuracy check pipeline

Signed-off-by: Kim, Vinnam <vinnam.kim@intel.com>

examples/experimental/onnx/accuracy_checker.py

@@ -0,0 +1,38 @@
+"""
+ Copyright (c) 2022 Intel Corporation
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+      http://www.apache.org/licenses/LICENSE-2.0
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+"""
+
+from openvino.tools.accuracy_checker.annotation_converters.ms_coco import COCO_TO_VOC, MSCocoSegmentationConverter
+from openvino.tools.accuracy_checker.main import main
+
+
+class MSCocoSegmentationToVOCConverter(MSCocoSegmentationConverter):
+    __provider__ = 'mscoco_segmentation_to_voc'
+
+    @staticmethod
+    def _read_image_annotation(image, annotations, label_id_to_label):
+        image_labels, is_crowd, segmentation_polygons = MSCocoSegmentationConverter._read_image_annotation(
+            image, annotations, label_id_to_label)
+
+        # Convert to VOC labels
+        image_labels = MSCocoSegmentationToVOCConverter.convert_to_voc(
+            image_labels)
+
+        return image_labels, is_crowd, segmentation_polygons
+
+    @staticmethod
+    def convert_to_voc(image_labels):
+        return [COCO_TO_VOC[label] if label in COCO_TO_VOC else 0 for label in image_labels]
+
+
+if __name__ == "__main__":
+    main()

examples/experimental/onnx/det_and_seg/onnx_models_configs/fcn-resnet50-12.yml

@@ -9,13 +9,13 @@ models:
     datasets:
       - name: mscoco_segmentation_to_voc
         annotation_conversion:
-          converter: mscoco_segmentation
+          converter: mscoco_segmentation_to_voc
           annotation_file: annotations/instances_val2017.json
           has_background: True
           sort_annotations: True
           semantic_only: True
           # This should be an absolute path
-          masks_dir: /mnt/ssd2/omz_data/val2017/segmentation_masks
+          masks_dir: segmentation_masks
           # Only evaluate on VOC labels
           convert_COCO_to_VOC_labels: True
         annotation: mscoco_segmentation_to_voc.pickle

examples/experimental/onnx/run_ptq_onnx_models.sh

@@ -45,7 +45,7 @@ for config in `ls $CONFIGS_DIR`; do
 
     echo "2) Check model accuracy for $model_name (original)"
     # Accuracy check for the original model
-    accuracy_check  \
+    python $SCRIPT_DIR/accuracy_checker.py  \
         -c $CONFIGS_DIR/$config                     \
         -ss $NUMBER_OF_SAMPLES                      \
         -m $MODEL_DIR/$model_name.onnx              \
@@ -56,7 +56,7 @@ for config in `ls $CONFIGS_DIR`; do
 
     echo "3) Check model accuracy for $model_name (quantized)"
     # Accuracy check for the quantized model
-    accuracy_check  \
+    python $SCRIPT_DIR/accuracy_checker.py  \
         -c $CONFIGS_DIR/$config                     \
         -ss $NUMBER_OF_SAMPLES                      \
         -m $OUTPUT_DIR/$model_name-quantized.onnx   \